jm + sanitisation   2

HSE data releases may be de-anonymisable
Although the data has been kept anonymous, the increasing sophistication of computer-driven data-mining techniques has led to fears patients could be identified.
A HSE spokesman confirmed yesterday that the office responded to requests for data from a variety of sources, including researchers, the universities, GPs, the media, health insurers and pharmaceutical companies. An average of about two requests a week was received. [...]
The information provided by the HPO has significant patient identifiers removed, such as name and date of birth. According to the HSE spokesman, individual patient information is not provided and, where information is sought for a small group of patients, this is not provided where the number involved is under five. “In such circumstances, it is highly unlikely that anyone could be identified. Nevertheless, we will have another look at data releases from the office,” he said.

I'd say this could be readily reversible, from the sounds of it.
anonymisation  sanitisation  data-dumps  hse  health  privacy  via:tjmcintyre 
june 2014 by jm
'Robust De-anonymization of Large Sparse Datasets' [pdf]
paper by Arvind Narayanan and Vitaly Shmatikov, 2008.

'We present a new class of statistical de- anonymization attacks against high-dimensional micro-data, such as individual preferences, recommendations, transaction records and so on. Our techniques are robust to perturbation in the data and tolerate some mistakes in the adversary's background knowledge. We apply our de-anonymization methodology to the Netflix Prize dataset, which contains anonymous movie ratings of 500,000 subscribers of Netflix, the world's largest online movie rental service. We demonstrate that an adversary who knows only a little bit about an individual subscriber can easily identify this subscriber's record in the dataset. Using the Internet Movie Database as the source of background knowledge, we successfully identified the Netflix records of known users, uncovering their apparent political preferences and other potentially sensitive information.'
anonymisation  anonymization  sanitisation  databases  data-dumps  privacy  security  papers 
june 2014 by jm

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